In any receiver system, the channel equalizer is an essential component, improving the bit error rate (BER) by correcting the received signal for the effects of the channel. Channel equalization is typically best performed using a decision feedback equalizer (DFE), especially if the channel has deep fades. Decision feedback equalizers consist of a forward adaptive transversal filter and a feedback adaptive transversal filter, with the equalized signal being the sum of the outputs of the two filters. The base-band received signal corrupted by multi-path interference is fed into the forward filter while decisions made on the equalized signal are fed back through the feedback filter.
As with virtually all channel equalizers, decision feedback equalizers are characterized by high computational complexity dependent on date rate, spectral efficiency, and rate of change for multi-path channels. Moreover, better decision feedback equalizer implementations employ large transversal filter lengths. Accordingly, decision feedback equalizers within high throughput systems such as digital television are typically designed as fixed-function application specific integrated circuit (ASIC) cores processing data on a sample-by-sample basis.
Fixed function ASIC implementation necessitates expensive redesign when an applicable standard evolves due to either new service requirements or the need for performance enhancement. Moreover, some applications such as software radio (SWR) require significant flexibility to adapt to different modulation formats and receiver signal processing algorithms. Combined with high throughput requirements and computationally expensive algorithms, such need for reconfigurability precludes economically viable hardware implementation of software radio.
There is, therefore, a need in the art for an improved decision feedback equalizer for use in channel equalization lowering computational complexity for the hardware employed while allowing improved reconfigurability.